Meta-QTL analysis for mining of candidate genes and constitutive gene network development for fungal disease resistance in maize (Zea mays L.)

Abstract

The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases. Over the last three decades, many quantitative trait loci (QTL) mapping studies reported numerous QTL for fungal disease resistance (FDR) in maize. However, different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies. The meta-QTL (MQTL) analysis is the meta-analysis of multiple QTL experiments, which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits. In the present study, 128 (33.59%) out of 381 reported QTL (from 82 studies) for FDR could be projected on the maize genome through MQTL analysis. It revealed 38 MQTL for FDR (12 diseases) on all chromosomes except chromosome 10. Five MQTL namely 1_4, 2_4, 3_2, 3_4, and 5_4 were linked with multiple FDR. Total of 1910 candidate genes were identified for all the MQTL regions, with protein kinase gene families, TFs, pathogenesis-related, and disease-responsive proteins directly or indirectly associated with FDR. The comparison of physical positions of marker-traits association (MTAs) from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases. The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies. The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network, which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.